Machine Learning Engineer

Machine Learning Engineer (Contract | Remote)Location: Remote (India or LATAM preferred)Contract: 6–12 months (extension likely)Start: ASAPOverviewWe are partnering with a large, enterprise-scale organization that is expanding its machine learning and AI capabilities as part of a broader data and digital transformation. The team is focused on building scalable, production-grade ML solutions that directly support business operations and decision-making.We are seeking a hands-on Machine Learning Engineer who is comfortable working across the full ML lifecycle from model development to deployment and optimization in a cloud environment.Key ResponsibilitiesDesign, build, train, and deploy machine learning models using PythonDevelop and maintain ML pipelines in Amazon SageMaker (training, tuning, deployment, monitoring)Collaborate closely with data engineers, analytics teams, and business stakeholders to translate requirements into ML solutionsSupport model experimentation, evaluation, and iteration to improve accuracy and performanceImplement best practices for model versioning, monitoring, and performance trackingContribute to GenAI and advanced analytics initiatives where applicableClearly communicate technical concepts, model outputs, and recommendations to non-technical stakeholdersRequired Skills & ExperienceStrong experience as a Machine Learning Engineer or similar roleHands-on expertise with Amazon SageMakerStrong proficiency in Python for ML developmentExperience deploying models into production environmentsAbility to work independently in a remote, enterprise settingStrong communication skills and stakeholder-facing experienceNice to HaveExperience with GenAI / LLM-based solutionsFamiliarity with MLOps concepts (model monitoring, drift detection, retraining)Experience integrating ML models with data pipelines or APIsPrior experience in large-scale or regulated enterprise environmentsWhy ApplyLong-term contract with strong extension potentialOpportunity to work on real, production ML systemsExposure to AI, ML, and GenAI initiatives at enterprise scaleFully remote role with flexible working environmentHow to ApplyApply with your CV or LinkedIn profile. Shortlisted candidates will be contacted for an initial discussion.

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